In: Alcohol and alcoholism: the international journal of the Medical Council on Alcoholism (MCA) and the journal of the European Society for Biomedical Research on Alcoholism (ESBRA), Band 48, Heft 2, S. 153-159
Aims: TheAmerican Diabetes Association, and the joint European Society of Cardiology and European Association for the Study of Diabetes guidelines recommend a resting ECG in people with type 2 diabetes with hypertension or suspected cardiovascular disease (CVD). However, knowledge on the prevalence of ECG abnormalities is incomplete. We aimed to analyse the prevalence of ECG abnormalities and their cross-sectional associations with cardiovascular risk factors in people with type 2 diabetes. Methods: We used data of the Diabetes Care System cohort obtained in 2018. ECG abnormalities were defined using the Minnesota Classification and categorised into types of abnormalities. The prevalence was calculated for the total population (n = 8068) and the subgroup of people without a history of CVD (n = 6494). Logistic regression models were used to asses cross-sectional associations. Results: Approximately one-third of the total population had minor (16.0%) or major (13.1%) ECG abnormalities. Of the participants without a CVD history, approximately one-quarter had minor (14.9%) ormajor (9.1%) ECG abnormalities, and for those with hypertension or very high CVD risk, the prevalencewas 27.5% and 39.6%, respectively. ECG abnormalities were significantly and consistently associated with established CVD risk factors. Conclusions: Resting ECG abnormalities are common in all people with type 2 diabetes (29.1%), including those without a history of CVD (24.0%), and their prevalence is related to traditional cardiovascular risk factors such as older age, male sex, hypertension, lower HDL cholesterol, higher BMI, and smoking behaviour. ; This article has been made possiblewith funding by the Dutch Heart Foundation grant CVON2017-15 RESCUED, the European Union's Horizon 2020 Research and Innovation Program under acronym ESCAPE-NET (registered under grant agreement No 733381) and Amsterdam University Medical Centers.
Background: Microalbuminuria is an early sign of kidney disease in people with diabetes and indicates increased risk of cardiovascular disease. We tested whether a urinary proteomic risk classifier (CKD273) score was associated with development of microalbuminuria and whether progression to microalbuminuria could be prevented with the mineralocorticoid receptor antagonist spironolactone. Methods: In this multicentre, prospective, observational study with embedded randomised controlled trial (PRIORITY), we recruited people with type 2 diabetes, normal urinary albumin excretion, and preserved renal function from 15 specialist centres in ten European countries. All participants (observational cohort) were tested with the CKD273 classifier and classified as high risk (CKD273 classifier score >0·154) or low risk (≤0·154). Participants who were classified as high risk were entered into a randomised controlled trial and randomly assigned (1:1), by use of an interactive web-response system, to receive spironolactone 25 mg once daily or matched placebo (trial cohort). The primary endpoint was development of confirmed microalbuminuria in all individuals with available data (observational cohort). Secondary endpoints included reduction in incidence of microalbuminuria with spironolactone (trial cohort, intention-to-treat population) and association between CKD273 risk score and measures of impaired renal function based on estimated glomerular filtration rate (eGFR; observational cohort). Adverse events (particularly gynaecomastia and hyperkalaemia) and serious adverse events were recorded for the intention-to-treat population (trial cohort). This study is registered with the EU Clinical Trials Register (EudraCT 20120-004523-4) and ClinicalTrials.gov (NCT02040441) and is completed. Findings: Between March 25, 2014, and Sept 30, 2018, we enrolled and followed-up 1775 participants (observational cohort), 1559 (88%) of 1775 participants had a low-risk urinary proteomic pattern and 216 (12%) had a high-risk pattern, of whom 209 were included in the trial cohort and assigned to spironolactone (n=102) or placebo (n=107). The overall median follow-up time was 2·51 years (IQR 2·0–3·0). Progression to microalbuminuria was seen in 61 (28%) of 216 high-risk participants and 139 (9%) of 1559 low-risk participants (hazard ratio [HR] 2·48, 95% CI 1·80–3·42; p<0·0001, after adjustment for baseline variables of age, sex, HbA1c, systolic blood pressure, retinopathy, urine albumin-to-creatinine ratio [UACR], and eGFR). Development of impaired renal function (eGFR <60 mL/min per 1·73 m2) was seen in 48 (26%) of 184 high-risk participants and 119 (8%) of 1423 low-risk participants (HR 3·50; 95% CI 2·50–4·90, after adjustment for baseline variables). A 30% decrease in eGFR from baseline (post-hoc endpoint) was seen in 42 (19%) of 216 high-risk participants and 62 (4%) of 1559 low-risk participants (HR 5·15, 95% CI 3·41–7·76; p<0·0001, after adjustment for basline eGFR and UACR). In the intention-to-treat trial cohort, development of microalbuminuria was seen in 35 (33%) of 107 in the placebo group and 26 (25%) of 102 in the spironolactone group (HR 0·81, 95% CI 0·49–1·34; p=0·41). In the safety analysis (intention-to-treat trial cohort), events of plasma potassium concentrations of more than 5·5 mmol/L were seen in 13 (13%) of 102 participants in the spironolactone group and four (4%) of 107 participants in the placebo group, and gynaecomastia was seen in three (3%) participants in the spironolactone group and none in the placebo group. One patient died in the placebo group due to a cardiac event (considered possibly related to study drug) and one patient died in the spironolactone group due to cancer, deemed unrelated to study drug. Interpretation: In people with type 2 diabetes and normoalbuminuria, a high-risk score from the urinary proteomic classifier CKD273 was associated with an increased risk of progression to microalbuminuria over a median of 2·5 years, independent of clinical characteristics. However, spironolactone did not prevent progression to microalbuminuria in high-risk patients. Funding: European Union Seventh Framework Programme.
In: Kengne , A P , Beulens , J W J , Peelen , L M , Moons , K G M , van der Schouw , Y T , Schulze , M B , Spijkerman , A M W , Griffin , S J , Grobbee , D E , Palla , L , Tormo , M J , Arriola , L , Barengo , N C , Barricarte , A , Boeing , H , Bonet , C , Clavel-Chapelon , F , Dartois , L , Fagherazzi , G , Franks , P W , Huerta , J M , Kaaks , R , Key , T J , Khaw , K T , Li , K , Mühlenbruch , K , Nilsson , P M , Overvad , K , Overvad , T F , Palli , D , Panico , S , Quirós , J R , Rolandsson , O , Roswall , N , Sacerdote , C , Sánchez , M J , Slimani , N , Tagliabue , G , Tjønneland , A , Tumino , R , van der A , D L , Forouhi , N G , Sharp , S J , Langenberg , C , Riboli , E & Wareham , N J 2014 , ' Non-invasive risk scores for prediction of type 2 diabetes (EPIC-InterAct) : A validation of existing models ' , The Lancet Diabetes and Endocrinology , vol. 2 , no. 1 , pp. 19-29 . https://doi.org/10.1016/S2213-8587(13)70103-7
Background: The comparative performance of existing models for prediction of type 2 diabetes across populations has not been investigated. We validated existing non-laboratory-based models and assessed variability in predictive performance in European populations. Methods: We selected non-invasive prediction models for incident diabetes developed in populations of European ancestry and validated them using data from the EPIC-InterAct case-cohort sample (27 779 individuals from eight European countries, of whom 12 403 had incident diabetes). We assessed model discrimination and calibration for the first 10 years of follow-up. The models were first adjusted to the country-specific diabetes incidence. We did the main analyses for each country and for subgroups defined by sex, age (0·05) except for three models. However, two models overestimated risk, DPoRT by 34% (95% CI 29-39%) and Cambridge by 40% (28-52%). Discrimination was always better in individuals younger than 60 years or with a low waist circumference than in those aged at least 60 years or with a large waist circumference. Patterns were inconsistent for BMI. All models overestimated risks for individuals with a BMI of <25 kg/m 2 . Calibration patterns were inconsistent for age and waist-circumference subgroups. Interpretation: Existing diabetes prediction models can be used to identify individuals at high risk of type 2 diabetes in the general population. However, the performance of each model varies with country, age, sex, and adiposity. Funding: The European Union.